1. Field of Invention
This invention is directed to image correlation systems.
2. Description of Related Art
Various known devices use images acquired by a sensor array, and correlation between images acquired by the sensor array, to determine deformations and/or displacements. For example, one class of such devices is based on acquiring a speckle image generated by illuminating an optically rough surface with a light source. Generally, the light source is a coherent light source, such as a laser-generating light source. Such laser-generating light sources include a laser, laser diode and the like. After the optically rough surface is illuminated by the light source the light scattered from the optically rough surface is imaged onto an optical sensor. The optical sensor can be a charge-couple device (CCD), or a semi-conductor image sensor array, such as a CMOS image sensor array or the like.
Prior to displacing or deforming the optically rough surface, a first or reference speckle image is captured and stored. Then, after displacing or deforming the optically rough surface, a second or subsequent speckle image is captured and stored. The reference and second speckle images are then compared on a pixel-by-pixel basis. In general, a plurality of comparisons are performed. In each comparison, the reference and second speckle images are offset, or spatially translated, relative to each other. Between each comparison, the amount of offset, or spatial translation, is increased by a known amount, such as one image element, pixel, or an integer number of image elements or pixels.
In each comparison, the image value of a particular pixel in the reference image is multiplied by, or subtracted from, the image value of the corresponding second image pixel, where the corresponding second image pixel is determined based on the amount of offset. The value resulting from each pixel-by-pixel operation is accumulated to determine a correlation value for that comparison between the reference and second images. That correlation value is then, in effect, plotted against the offset amount, or spatial translation position, for that comparison to determine a correlation function value point. The offset having the greatest correlation between the reference and first images will generate a peak, or a trough, depending on how the pixel-by-pixel comparison is performed, in the plot of correlation function value points. The offset amount corresponding to the peak or trough represents the amount of displacement or deformation between the reference and second speckle images.
In image correlation systems where sub-pixel resolution and accuracy is needed, the sub-pixel resolution is obtained by sub-pixel interpolation. In known laboratory-type systems, sub-pixel interpolation is conventionally performed by fitting a continuous function to the discrete pixel-by-pixel points of a conventional cross-correlation function, locating the extremum, or peak, of the fitted function with sub-pixel resolution, and assuming the extremum or peak, location is the best estimate of the true offset between the reference and second images, and thus of the associated displacement. It is also known to apply a similar procedure to synthetic images that are created at sub-pixel steps by interpolating between the adjacent raw pixel values to create synthetic pixel values, as though an image were taken with the pixels located at the desired sub-pixel location.
In conventional image correlation systems and high-accuracy laboratory systems where sub-pixel resolution is needed, systematic displacement errors within a sub-pixel are introduced when determining a displacement between the reference image and the second image to a sub-pixel resolution. For example, systematic displacement errors caused by an interpolation method used in a cross-correlation algorithm can be introduced into the sub-pixel image correlation. Systematic errors in determining the displacement can be influenced by many factors, such as the frequency content of the speckle pattern, amplitude attenuation and the phase error of the interpolator used in the correlation. Systematic errors in determining the displacement can also be influenced by the type of interpolation function used to model the correlation function, such as linear, quadratic, Gaussian, etc.
U.S. patent application Ser. No. 09/731,671 which is incorporated herein by reference, discloses systems and methods for high/accuracy displacement determination in a correlation-based position transducer. In the 671 application, a system is provided that estimates the sub-pixel displacement of images in correlation-based position transducers and the like. The system then rejects the systematic displacement estimation errors present when conventional sub-pixel estimation methods are applied to a number of correlation function value points, especially when the correlation function value points are arranged asymmetrically. However, the systems and methods disclosed in the 671 application fail to reduce the accumulation of any systematic displacement errors which may be present when determining the relative position of a current reference speckle image and a new reference speckle image.
U.S. Pat. No. 967,093 to Takemori discloses systems and methods for measuring deformation of an object using speckle image correlation. In particular, Takemori describes various conventional methods for comparing two speckle images, and for determining when to update a current reference speckle image with a new reference speckle image. However, the methods of Takemori fail to recognize, or account for, the systematic displacement errors which may be present when determining the relative position of a current reference speckle image and a new reference speckle image. Furthermore, Takemori does not indicate any method of compensating or selecting reference speckle images with good sub-pixel accuracy and resolution. Accordingly, the measurements provided by the system in Takemori incorporate the accumulation of systematic displacement errors.
Japanese Patent Application JP 07069302 to Kamegawa discloses a speckle-image based displacement meter and method that reduces the error accumulation by storing a series of reference images, and by recalling selected ones of those reference images as comparison images that correspond to an appropriate displacement storing operation of the displacement meter. In comparison to previous conventional methods, the method of JP 07069302 reduces certain displacement errors which would otherwise accumulate over extended displacement ranges. However, the methods of JP 07069302 fail to recognize or account for the systematic displacement errors which may be present when determining the relative position of one reference image relative to another reference image. Furthermore, JP 07069302 does not disclose any method of compensating or selecting reference speckle images with good sub-pixel accuracy and resolution. Accordingly, the measurements from the image correlation system in JP 07069302 either must be made using an external displacement reference or systematic displacement errors will accumulate if an external reference is not used when obtaining the series of reference images.
In the article, “Systematic Errors in Digital Image Correlation Caused by Intensity Interpolation,” by Hubert Schreier, systematic displacement errors are described which correspond to the method of sub-pixel image correlation applied to speckle images. Furthermore, the article discloses information relating to reducing the magnitudes of the systematic displacement errors themselves. However, Schreier does not disclose or suggest any method for determining or selecting the relative displacements between a set of reference images so that the systematic displacement errors may be compensated for, or controlled for, for displacement ranges beyond one image frame.